Bacterial biofilms are major causes of chronic infections and medical-device-associated infections. Their persistence and resistance to antibiotics and host immunity impose substantial clinical and economic burdens. Non-invasive, dynamic, and quantitative characterization of biofilms is therefore essential for anti-infective research, drug development, and clinical risk assessment. Electrochemical impedance spectroscopy (EIS) has been widely used for biofilm monitoring because it is real-time, in situ, and non-destructive. However, EIS interpretation remains dominated by equivalent circuit models, which simplify biofilms into ideal electrical elements. Although equivalent circuit models are intuitive and convenient, they have fundamental limitations: fitted parameters often lack clear physical meaning; different circuit topologies can fit the same spectrum; model selection is subjective; and the models have limited predictive power and cannot directly retrieve intrinsic biophysical properties. These limitations restrict EIS from advancing from status monitoring to mechanistic interpretation. Transmission-line models, dielectric-spectrum theory, and machine-learning approaches have been attempted, but a unified theoretical framework that quantitatively links the multi-dimensional physical properties of biofilms to broadband impedance responses is still lacking. This review systematically examines the progress and bottlenecks of biofilm impedance analysis and proposes a physics-driven paradigm. The central hypothesis is that, within an appropriate frequency window, an interfacial biofilm can be approximated as a quasi-homogeneous dielectric membrane. This approximation does not deny microscopic heterogeneity; rather, it assumes that when the characteristic spatial scale of the applied field is much larger than that of local cellular aggregates, pores, and extracellular polymeric substances, the biofilm behaves as a continuous dielectric medium governed mainly by dielectric polarization and ionic migration rather than by faradaic electrochemical reactions. On this basis, a minimal operable physical model is constructed using Maxwell""s equations, dielectric relaxation theory, and thermodynamic constraints. The model adopts an electrode-biofilm-electrolyte geometry with appropriate boundary conditions and a frequency-dependent complex permittivity. Combined with physical priors and Bayesian inversion, it aims to retrieve a minimal set of intrinsic quantities from EIS data: biofilm thickness, biomass, conductivity, dielectric constant, and interfacial adhesion-related equivalent electromagnetic characteristics. These parameters can be independently cross-validated by confocal laser scanning microscopy, quartz crystal microbalance, conductivity measurements, and microfluidic mechanical assays, and can be correlated with biological features such as metabolic activity, three-dimensional structure, mechanical properties, interfacial stability, and stress resistance. Compared with conventional equivalent circuit models, the proposed framework offers clearer physical definitions, improved inversion uniqueness through physical constraints such as Kramers-Kronig consistency, predictive capability through the evolution of physical parameters, and compatibility with independent non-electrochemical validation. Because multi-parameter inversion from limited-band EIS data is inherently ill-posed, the framework requires physical priors, multi-frequency measurements, orthogonal experimental calibration, and multimodal constraints to reduce parameter coupling and non-uniqueness. The validity of the quasi-homogeneous approximation must be further defined for highly heterogeneous, disrupted, or non-continuous biofilms, and the retrieved parameters must be cross-checked across strains and culture conditions. Nevertheless, this physics-based paradigm may enable EIS to provide quantitative physical portraits of biofilms rather than merely indicating whether biofilms are present or increasing. It may also be extended to cell monolayers, stem-cell layers, organoid sheets, and other two-dimensional interfacial living systems, offering a new theoretical route for spectroscopic characterization of biological interfaces.